code: def test_fit_ndarrays():
      X = np.ones((10, 5))
      y = np.concatenate([np.zeros(5), np.ones(5)])
  
      sgd = SGDClassifier(tol=1e-3)
      inc = Incremental(sgd)
  
      inc.partial_fit(X, y, classes=[0, 1])
      sgd.fit(X, y)
  
      assert inc.estimator is sgd
      assert_eq(inc.coef_, inc.estimator_.coef_)
  
imports: import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  import sklearn.datasets
  import sklearn.model_selection
  from dask.array.utils import assert_eq
  from scipy.sparse import csr_matrix
  from sklearn.base import clone
  from sklearn.linear_model import SGDClassifier, SGDRegressor
  from sklearn.pipeline import make_pipeline
  import dask_ml.feature_extraction.text
  import dask_ml.metrics
  from dask_ml.metrics.scorer import check_scoring
  from dask_ml.wrappers import Incremental
label_desc: Use image node_id 7 for calling a global function with example usage: test_fit_ndarrays() without return types